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import os | |
import sys | |
import json | |
import argparse | |
import subprocess | |
import spaces | |
now_dir = os.getcwd() | |
sys.path.append(now_dir) | |
from rvc.configs.config import Config | |
from rvc.lib.tools.prerequisites_download import prequisites_download_pipeline | |
from rvc.infer.infer import infer_pipeline | |
from rvc.lib.tools.model_download import model_download_pipeline | |
config = Config() | |
current_script_directory = os.path.dirname(os.path.realpath(__file__)) | |
logs_path = os.path.join(current_script_directory, "logs") | |
# Get TTS Voices | |
with open(os.path.join("rvc", "lib", "tools", "tts_voices.json"), "r") as f: | |
voices_data = json.load(f) | |
locales = list({voice["Locale"] for voice in voices_data}) | |
# Infer | |
def run_infer_script( | |
f0up_key, | |
filter_radius, | |
index_rate, | |
rms_mix_rate, | |
protect, | |
hop_length, | |
f0method, | |
input_path, | |
output_path, | |
pth_path, | |
index_path, | |
split_audio, | |
f0autotune, | |
clean_audio, | |
clean_strength, | |
export_format, | |
embedder_model, | |
embedder_model_custom, | |
upscale_audio, | |
): | |
f0autotune = "True" if str(f0autotune) == "True" else "False" | |
clean_audio = "True" if str(clean_audio) == "True" else "False" | |
upscale_audio = "True" if str(upscale_audio) == "True" else "False" | |
infer_pipeline( | |
f0up_key, | |
filter_radius, | |
index_rate, | |
rms_mix_rate, | |
protect, | |
hop_length, | |
f0method, | |
input_path, | |
output_path, | |
pth_path, | |
index_path, | |
split_audio, | |
f0autotune, | |
clean_audio, | |
clean_strength, | |
export_format, | |
embedder_model, | |
embedder_model_custom, | |
upscale_audio, | |
) | |
return f"File {input_path} inferred successfully.", output_path.replace( | |
".wav", f".{export_format.lower()}" | |
) | |
# Batch infer | |
def run_batch_infer_script( | |
f0up_key, | |
filter_radius, | |
index_rate, | |
rms_mix_rate, | |
protect, | |
hop_length, | |
f0method, | |
input_folder, | |
output_folder, | |
pth_path, | |
index_path, | |
split_audio, | |
f0autotune, | |
clean_audio, | |
clean_strength, | |
export_format, | |
embedder_model, | |
embedder_model_custom, | |
upscale_audio, | |
): | |
f0autotune = "True" if str(f0autotune) == "True" else "False" | |
clean_audio = "True" if str(clean_audio) == "True" else "False" | |
upscale_audio = "True" if str(upscale_audio) == "True" else "False" | |
audio_files = [ | |
f for f in os.listdir(input_folder) if f.endswith((".mp3", ".wav", ".flac")) | |
] | |
print(f"Detected {len(audio_files)} audio files for inference.") | |
for audio_file in audio_files: | |
if "_output" in audio_file: | |
pass | |
else: | |
input_path = os.path.join(input_folder, audio_file) | |
output_file_name = os.path.splitext(os.path.basename(audio_file))[0] | |
output_path = os.path.join( | |
output_folder, | |
f"{output_file_name}_output{os.path.splitext(audio_file)[1]}", | |
) | |
print(f"Inferring {input_path}...") | |
infer_pipeline( | |
f0up_key, | |
filter_radius, | |
index_rate, | |
rms_mix_rate, | |
protect, | |
hop_length, | |
f0method, | |
input_path, | |
output_path, | |
pth_path, | |
index_path, | |
split_audio, | |
f0autotune, | |
clean_audio, | |
clean_strength, | |
export_format, | |
embedder_model, | |
embedder_model_custom, | |
upscale_audio, | |
) | |
return f"Files from {input_folder} inferred successfully." | |
# TTS | |
def run_tts_script( | |
tts_text, | |
tts_voice, | |
tts_rate, | |
f0up_key, | |
filter_radius, | |
index_rate, | |
rms_mix_rate, | |
protect, | |
hop_length, | |
f0method, | |
output_tts_path, | |
output_rvc_path, | |
pth_path, | |
index_path, | |
split_audio, | |
f0autotune, | |
clean_audio, | |
clean_strength, | |
export_format, | |
embedder_model, | |
embedder_model_custom, | |
upscale_audio, | |
): | |
f0autotune = "True" if str(f0autotune) == "True" else "False" | |
clean_audio = "True" if str(clean_audio) == "True" else "False" | |
upscale_audio = "True" if str(upscale_audio) == "True" else "False" | |
tts_script_path = os.path.join("rvc", "lib", "tools", "tts.py") | |
if os.path.exists(output_tts_path): | |
os.remove(output_tts_path) | |
command_tts = [ | |
"python", | |
tts_script_path, | |
tts_text, | |
tts_voice, | |
str(tts_rate), | |
output_tts_path, | |
] | |
subprocess.run(command_tts) | |
infer_pipeline( | |
f0up_key, | |
filter_radius, | |
index_rate, | |
rms_mix_rate, | |
protect, | |
hop_length, | |
f0method, | |
output_tts_path, | |
output_rvc_path, | |
pth_path, | |
index_path, | |
split_audio, | |
f0autotune, | |
clean_audio, | |
clean_strength, | |
export_format, | |
embedder_model, | |
embedder_model_custom, | |
upscale_audio, | |
) | |
return f"Text {tts_text} synthesized successfully.", output_rvc_path.replace( | |
".wav", f".{export_format.lower()}" | |
) | |
# Download | |
def run_download_script(model_link): | |
model_download_pipeline(model_link) | |
return f"Model downloaded successfully." | |
# Prerequisites | |
def run_prerequisites_script(pretraineds_v1, pretraineds_v2, models, exe): | |
prequisites_download_pipeline(pretraineds_v1, pretraineds_v2, models, exe) | |
return "Prerequisites installed successfully." | |
# Parse arguments | |
def parse_arguments(): | |
parser = argparse.ArgumentParser( | |
description="Run the main.py script with specific parameters." | |
) | |
subparsers = parser.add_subparsers( | |
title="subcommands", dest="mode", help="Choose a mode" | |
) | |
# Parser for 'infer' mode | |
infer_parser = subparsers.add_parser("infer", help="Run inference") | |
infer_parser.add_argument( | |
"--f0up_key", | |
type=str, | |
help="Value for f0up_key", | |
choices=[str(i) for i in range(-24, 25)], | |
default="0", | |
) | |
infer_parser.add_argument( | |
"--filter_radius", | |
type=str, | |
help="Value for filter_radius", | |
choices=[str(i) for i in range(11)], | |
default="3", | |
) | |
infer_parser.add_argument( | |
"--index_rate", | |
type=str, | |
help="Value for index_rate", | |
choices=[str(i / 10) for i in range(11)], | |
default="0.3", | |
) | |
infer_parser.add_argument( | |
"--rms_mix_rate", | |
type=str, | |
help="Value for rms_mix_rate", | |
choices=[str(i / 10) for i in range(11)], | |
default="1", | |
) | |
infer_parser.add_argument( | |
"--protect", | |
type=str, | |
help="Value for protect", | |
choices=[str(i / 10) for i in range(6)], | |
default="0.33", | |
) | |
infer_parser.add_argument( | |
"--hop_length", | |
type=str, | |
help="Value for hop_length", | |
choices=[str(i) for i in range(1, 513)], | |
default="128", | |
) | |
infer_parser.add_argument( | |
"--f0method", | |
type=str, | |
help="Value for f0method", | |
choices=[ | |
"pm", | |
"harvest", | |
"dio", | |
"crepe", | |
"crepe-tiny", | |
"rmvpe", | |
"fcpe", | |
"hybrid[crepe+rmvpe]", | |
"hybrid[crepe+fcpe]", | |
"hybrid[rmvpe+fcpe]", | |
"hybrid[crepe+rmvpe+fcpe]", | |
], | |
default="rmvpe", | |
) | |
infer_parser.add_argument("--input_path", type=str, help="Input path") | |
infer_parser.add_argument("--output_path", type=str, help="Output path") | |
infer_parser.add_argument("--pth_path", type=str, help="Path to the .pth file") | |
infer_parser.add_argument( | |
"--index_path", | |
type=str, | |
help="Path to the .index file", | |
) | |
infer_parser.add_argument( | |
"--split_audio", | |
type=str, | |
help="Enable split audio", | |
choices=["True", "False"], | |
default="False", | |
) | |
infer_parser.add_argument( | |
"--f0autotune", | |
type=str, | |
help="Enable autotune", | |
choices=["True", "False"], | |
default="False", | |
) | |
infer_parser.add_argument( | |
"--clean_audio", | |
type=str, | |
help="Enable clean audio", | |
choices=["True", "False"], | |
default="False", | |
) | |
infer_parser.add_argument( | |
"--clean_strength", | |
type=str, | |
help="Value for clean_strength", | |
choices=[str(i / 10) for i in range(11)], | |
default="0.7", | |
) | |
infer_parser.add_argument( | |
"--export_format", | |
type=str, | |
help="Export format", | |
choices=["WAV", "MP3", "FLAC", "OGG", "M4A"], | |
default="WAV", | |
) | |
infer_parser.add_argument( | |
"--embedder_model", | |
type=str, | |
help="Embedder model", | |
choices=["contentvec", "hubert", "custom"], | |
default="hubert", | |
) | |
infer_parser.add_argument( | |
"--embedder_model_custom", | |
type=str, | |
help="Custom Embedder model", | |
default=None, | |
) | |
infer_parser.add_argument( | |
"--upscale_audio", | |
type=str, | |
help="Enable audio upscaling", | |
choices=["True", "False"], | |
default="False", | |
) | |
# Parser for 'batch_infer' mode | |
batch_infer_parser = subparsers.add_parser( | |
"batch_infer", help="Run batch inference" | |
) | |
batch_infer_parser.add_argument( | |
"--f0up_key", | |
type=str, | |
help="Value for f0up_key", | |
choices=[str(i) for i in range(-24, 25)], | |
default="0", | |
) | |
batch_infer_parser.add_argument( | |
"--filter_radius", | |
type=str, | |
help="Value for filter_radius", | |
choices=[str(i) for i in range(11)], | |
default="3", | |
) | |
batch_infer_parser.add_argument( | |
"--index_rate", | |
type=str, | |
help="Value for index_rate", | |
choices=[str(i / 10) for i in range(11)], | |
default="0.3", | |
) | |
batch_infer_parser.add_argument( | |
"--rms_mix_rate", | |
type=str, | |
help="Value for rms_mix_rate", | |
choices=[str(i / 10) for i in range(11)], | |
default="1", | |
) | |
batch_infer_parser.add_argument( | |
"--protect", | |
type=str, | |
help="Value for protect", | |
choices=[str(i / 10) for i in range(6)], | |
default="0.33", | |
) | |
batch_infer_parser.add_argument( | |
"--hop_length", | |
type=str, | |
help="Value for hop_length", | |
choices=[str(i) for i in range(1, 513)], | |
default="128", | |
) | |
batch_infer_parser.add_argument( | |
"--f0method", | |
type=str, | |
help="Value for f0method", | |
choices=[ | |
"pm", | |
"harvest", | |
"dio", | |
"crepe", | |
"crepe-tiny", | |
"rmvpe", | |
"fcpe", | |
"hybrid[crepe+rmvpe]", | |
"hybrid[crepe+fcpe]", | |
"hybrid[rmvpe+fcpe]", | |
"hybrid[crepe+rmvpe+fcpe]", | |
], | |
default="rmvpe", | |
) | |
batch_infer_parser.add_argument("--input_folder", type=str, help="Input folder") | |
batch_infer_parser.add_argument("--output_folder", type=str, help="Output folder") | |
batch_infer_parser.add_argument( | |
"--pth_path", type=str, help="Path to the .pth file" | |
) | |
batch_infer_parser.add_argument( | |
"--index_path", | |
type=str, | |
help="Path to the .index file", | |
) | |
batch_infer_parser.add_argument( | |
"--split_audio", | |
type=str, | |
help="Enable split audio", | |
choices=["True", "False"], | |
default="False", | |
) | |
batch_infer_parser.add_argument( | |
"--f0autotune", | |
type=str, | |
help="Enable autotune", | |
choices=["True", "False"], | |
default="False", | |
) | |
batch_infer_parser.add_argument( | |
"--clean_audio", | |
type=str, | |
help="Enable clean audio", | |
choices=["True", "False"], | |
default="False", | |
) | |
batch_infer_parser.add_argument( | |
"--clean_strength", | |
type=str, | |
help="Value for clean_strength", | |
choices=[str(i / 10) for i in range(11)], | |
default="0.7", | |
) | |
batch_infer_parser.add_argument( | |
"--export_format", | |
type=str, | |
help="Export format", | |
choices=["WAV", "MP3", "FLAC", "OGG", "M4A"], | |
default="WAV", | |
) | |
batch_infer_parser.add_argument( | |
"--embedder_model", | |
type=str, | |
help="Embedder model", | |
choices=["contentvec", "hubert", "custom"], | |
default="hubert", | |
) | |
batch_infer_parser.add_argument( | |
"--embedder_model_custom", | |
type=str, | |
help="Custom Embedder model", | |
default=None, | |
) | |
batch_infer_parser.add_argument( | |
"--upscale_audio", | |
type=str, | |
help="Enable audio upscaling", | |
choices=["True", "False"], | |
default="False", | |
) | |
# Parser for 'tts' mode | |
tts_parser = subparsers.add_parser("tts", help="Run TTS") | |
tts_parser.add_argument( | |
"--tts_text", | |
type=str, | |
help="Text to be synthesized", | |
) | |
tts_parser.add_argument( | |
"--tts_voice", | |
type=str, | |
help="Voice to be used", | |
choices=locales, | |
) | |
tts_parser.add_argument( | |
"--tts_rate", | |
type=str, | |
help="Increase or decrease TTS speed", | |
choices=[str(i) for i in range(-100, 100)], | |
default="0", | |
) | |
tts_parser.add_argument( | |
"--f0up_key", | |
type=str, | |
help="Value for f0up_key", | |
choices=[str(i) for i in range(-24, 25)], | |
default="0", | |
) | |
tts_parser.add_argument( | |
"--filter_radius", | |
type=str, | |
help="Value for filter_radius", | |
choices=[str(i) for i in range(11)], | |
default="3", | |
) | |
tts_parser.add_argument( | |
"--index_rate", | |
type=str, | |
help="Value for index_rate", | |
choices=[str(i / 10) for i in range(11)], | |
default="0.3", | |
) | |
tts_parser.add_argument( | |
"--rms_mix_rate", | |
type=str, | |
help="Value for rms_mix_rate", | |
choices=[str(i / 10) for i in range(11)], | |
default="1", | |
) | |
tts_parser.add_argument( | |
"--protect", | |
type=str, | |
help="Value for protect", | |
choices=[str(i / 10) for i in range(6)], | |
default="0.33", | |
) | |
tts_parser.add_argument( | |
"--hop_length", | |
type=str, | |
help="Value for hop_length", | |
choices=[str(i) for i in range(1, 513)], | |
default="128", | |
) | |
tts_parser.add_argument( | |
"--f0method", | |
type=str, | |
help="Value for f0method", | |
choices=[ | |
"pm", | |
"harvest", | |
"dio", | |
"crepe", | |
"crepe-tiny", | |
"rmvpe", | |
"fcpe", | |
"hybrid[crepe+rmvpe]", | |
"hybrid[crepe+fcpe]", | |
"hybrid[rmvpe+fcpe]", | |
"hybrid[crepe+rmvpe+fcpe]", | |
], | |
default="rmvpe", | |
) | |
tts_parser.add_argument("--output_tts_path", type=str, help="Output tts path") | |
tts_parser.add_argument("--output_rvc_path", type=str, help="Output rvc path") | |
tts_parser.add_argument("--pth_path", type=str, help="Path to the .pth file") | |
tts_parser.add_argument( | |
"--index_path", | |
type=str, | |
help="Path to the .index file", | |
) | |
tts_parser.add_argument( | |
"--split_audio", | |
type=str, | |
help="Enable split audio", | |
choices=["True", "False"], | |
default="False", | |
) | |
tts_parser.add_argument( | |
"--f0autotune", | |
type=str, | |
help="Enable autotune", | |
choices=["True", "False"], | |
default="False", | |
) | |
tts_parser.add_argument( | |
"--clean_audio", | |
type=str, | |
help="Enable clean audio", | |
choices=["True", "False"], | |
default="False", | |
) | |
tts_parser.add_argument( | |
"--clean_strength", | |
type=str, | |
help="Value for clean_strength", | |
choices=[str(i / 10) for i in range(11)], | |
default="0.7", | |
) | |
tts_parser.add_argument( | |
"--export_format", | |
type=str, | |
help="Export format", | |
choices=["WAV", "MP3", "FLAC", "OGG", "M4A"], | |
default="WAV", | |
) | |
tts_parser.add_argument( | |
"--embedder_model", | |
type=str, | |
help="Embedder model", | |
choices=["contentvec", "hubert", "custom"], | |
default="hubert", | |
) | |
tts_parser.add_argument( | |
"--embedder_model_custom", | |
type=str, | |
help="Custom Embedder model", | |
default=None, | |
) | |
tts_parser.add_argument( | |
"--upscale_audio", | |
type=str, | |
help="Enable audio upscaling", | |
choices=["True", "False"], | |
default="False", | |
) | |
# Parser for 'download' mode | |
download_parser = subparsers.add_parser("download", help="Download models") | |
download_parser.add_argument( | |
"--model_link", | |
type=str, | |
help="Link of the model", | |
) | |
# Parser for 'prerequisites' mode | |
prerequisites_parser = subparsers.add_parser( | |
"prerequisites", help="Install prerequisites" | |
) | |
prerequisites_parser.add_argument( | |
"--pretraineds_v1", | |
type=str, | |
choices=["True", "False"], | |
default="True", | |
help="Download pretrained models for v1", | |
) | |
prerequisites_parser.add_argument( | |
"--pretraineds_v2", | |
type=str, | |
choices=["True", "False"], | |
default="True", | |
help="Download pretrained models for v2", | |
) | |
prerequisites_parser.add_argument( | |
"--models", | |
type=str, | |
choices=["True", "False"], | |
default="True", | |
help="Donwload models", | |
) | |
prerequisites_parser.add_argument( | |
"--exe", | |
type=str, | |
choices=["True", "False"], | |
default="True", | |
help="Download executables", | |
) | |
return parser.parse_args() | |
def main(): | |
if len(sys.argv) == 1: | |
print("Please run the script with '-h' for more information.") | |
sys.exit(1) | |
args = parse_arguments() | |
try: | |
if args.mode == "infer": | |
run_infer_script( | |
str(args.f0up_key), | |
str(args.filter_radius), | |
str(args.index_rate), | |
str(args.rms_mix_rate), | |
str(args.protect), | |
str(args.hop_length), | |
str(args.f0method), | |
str(args.input_path), | |
str(args.output_path), | |
str(args.pth_path), | |
str(args.index_path), | |
str(args.split_audio), | |
str(args.f0autotune), | |
str(args.clean_audio), | |
str(args.clean_strength), | |
str(args.export_format), | |
str(args.embedder_model), | |
str(args.embedder_model_custom), | |
str(args.upscale_audio), | |
) | |
elif args.mode == "batch_infer": | |
run_batch_infer_script( | |
str(args.f0up_key), | |
str(args.filter_radius), | |
str(args.index_rate), | |
str(args.rms_mix_rate), | |
str(args.protect), | |
str(args.hop_length), | |
str(args.f0method), | |
str(args.input_folder), | |
str(args.output_folder), | |
str(args.pth_path), | |
str(args.index_path), | |
str(args.split_audio), | |
str(args.f0autotune), | |
str(args.clean_audio), | |
str(args.clean_strength), | |
str(args.export_format), | |
str(args.embedder_model), | |
str(args.embedder_model_custom), | |
str(args.upscale_audio), | |
) | |
elif args.mode == "tts": | |
run_tts_script( | |
str(args.tts_text), | |
str(args.tts_voice), | |
str(args.tts_rate), | |
str(args.f0up_key), | |
str(args.filter_radius), | |
str(args.index_rate), | |
str(args.rms_mix_rate), | |
str(args.protect), | |
str(args.hop_length), | |
str(args.f0method), | |
str(args.output_tts_path), | |
str(args.output_rvc_path), | |
str(args.pth_path), | |
str(args.index_path), | |
str(args.split_audio), | |
str(args.f0autotune), | |
str(args.clean_audio), | |
str(args.clean_strength), | |
str(args.export_format), | |
str(args.embedder_model), | |
str(args.embedder_model_custom), | |
str(args.upscale_audio), | |
) | |
elif args.mode == "download": | |
run_download_script( | |
str(args.model_link), | |
) | |
elif args.mode == "prerequisites": | |
run_prerequisites_script( | |
str(args.pretraineds_v1), | |
str(args.pretraineds_v2), | |
str(args.models), | |
str(args.exe), | |
) | |
except Exception as error: | |
print(f"Error: {error}") | |
if __name__ == "__main__": | |
main() | |